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If you’re running AdWords campaigns, chances are you’ve at least sniffed around the Google Display Network (GDN), which is a sort of entrée into display advertising with a familiar interface. The GDN has its share of detractors, to be sure, but it’s important to keep in mind what it is and what it isn’t.
The Google Display Network is potentially a great source of low-cost traffic and a demand-generation channel. Although it can work for direct response, it’s best for adding volume to a brand’s funnel. And the targeting, though it offers plenty of possibilities for optimization, isn’t as robust as search targeting.
As with any other channel, a loosely run GDN campaign can blow through a budget without a lot to show for it. In this whitepaper, we’ll show you how to use goals, audience knowledge, targeting, ad best practices, and our own preferred campaign strategy to make the GDN a powerful part of your purchasing funnel.
Let’s get into it.
Know Your Goals
Before you dive headlong into campaign set-up, what are your goals for the GDN? Start with your budget, and ask the following questions:
– Do you want more volume?
– Do you want a lower CPA?
– Do you want cheaper traffic?
– Do you have a retargeting strategy to re-engage your site’s visitors?
You must know the answers to these before you can custom-fit a bidding/targeting strategy. If you know the answers, by all means, read on.
Know Your Audience
Whether from market research, social media campaigns (Facebook campaigns are particularly good for this data), search campaigns, or any combination of the three, you should have a ton of data about your brand’s target audience. Some attributes that will specifically help your GDN targeting include:
-Demographics (age, gender)
-Interests and activities
-Needs – why should they/must they buy your product?
This data will help you create target personas and customize your messaging to match. Here’s an example, using the luxury/vintage furniture flash sale site One Kings Lane:
Armed with this kind of information, you can tailor very specific ads (image and text)… and you can tailor your targeting, which we’ll talk about now.
Know Your Targeting Types
First, a quick list of available GDN targeting (we’ll break each down separately):
KEYWORD CONTEXTUAL TARGETING
This kind of targeting allows you to specify keywords that trigger ads on relevant domains. Using our example persona above, we might target keywords like ‘vintage furniture’, ‘home décor’, ‘sofas’, ‘antique lamps’, etc. Google will find websites and webpages with content matching those keywords and show your ad to relevant users…most of the time! One of the most important tasks with this kind of targeting is scouring your data for sites that don’t fit contextually – and specifying them for exclusion.
This kind of targeting works very well in conjunction with placement targeting, which we’ll explain now.
This is exactly what it sounds like: you choose the websites (and sometimes individual pages) where you’d like your ads to appear. Once again, using our example persona, we might pick sites like Elle (for fashion and celebrity gossip), Southern Living (for décor), and Better Homes and Gardens (décor again).
Pro tip: you can use placement targeting and keyword targeting together to get ultra-relevant ad placement: for instance, you can specify Elle as a website to place your ads, but only on pages where keywords like “high end furniture,” “area rugs,” and “kitchen renovation” appear.
This is letting Google off sort of easy: you specify a topic (here, furniture or home décor) and let Google match your ads to a group of sites related to your topic. As Google itself says, “this is an easy way to get exposure,” but you’ll definitely want to go through and add exclusions as the data warrants, particularly if your goals are perfor- mance-based and don’t lean entirely on brand awareness.
Rather than targeting sites, this targets audiences whose interests align with your specified topics. Google uses online-behavior data to profile people’s interests, and the ads appear when those users are online. The interest may or may not match the sites on which the ads appear, so you may want to consider the user experience when turning these on.
GDN remarketing works like other forms of display remarketing: ads are served to people who have already visited your site. The ads can appear on any sites included within the GDN. Remarketing, of course, has proven more effective than traditional display ads because the ads are shown to users who have already expressed a certain level of intent.
The more granular you can get with your segmentation, the more effective your bidding can be. For instance, if you create segments for users who have visited your product pages (or, better yet, abandoned a shopping cart), you can a) serve them dynamic product ads and b) increase bids more dramatically than you would for users who simply visited your home page.
AGE AND GENDER TARGETING
This is just what it sounds like: you can exclude age ranges and genders that don’t match your target audience (for our home décor profile, we’d exclude men, for instance). One of our common practices is to exclude the lower and upper range of the available age groups, which have shown to be groups that purchase far less frequently than median-age groups.
Optimize Your Impressions
Okay, so now you understand your GDN targeting options. Let’s say you’ve created your initial settings and let the budget run for a bit to build up impressions. Then what?
You must keep an eye on both placement and demographic performance. Here’s how:
-Create a recurring production task to pull placement reports to look for bleeding/poor-performing placements
-Make sure you are collecting demographic data by incorporating all the ages and genders you are targeting in the display network tab
-Create a recurring production task to check demo data every couple of months and identify poor/top-performing demos
Optimize Your Ads
Now that we’ve covered targeting, let’s talk about the ads themselves. Ads for GDN should be as clear and upfront as possible.
GDN ads can be image-based or text-only. Let’s break them both down, starting with…
For image ads, always use these best practices:
-Choose top sellers, or products that generate the most clicks/interest on your site
-Include any deals or pricing-related messaging
-Use a call to action
For text-only ads, you should provide browsers with as much information as you can, including:
-What is the product/service?
-Any details to include?
-Why are we better than the others?
-Do we offer any special deals or discounts? Here’s a text ad that pretty much spells it out:
Since the browsers are in low-intent mode, we want to make sure they know exactly what they are getting into so as to prevent unnecessary clicks (and costs). This is a good time to note that, just as with search and social ads, you should never promise anything you can’t back up just to get the click.
USE THE CONVERSION OPTIMIZER!
If you’re optimizing campaigns by CPA (which is a very solid strategy if you’re not doing a sheer brand-awareness play), it’s simple: you should use the Conversion Optimizer. When it comes to the GDN, Google’s Conversion Optimizer algorithm has for more insight then we ever will.
There are a couple of best practices that we recommend:
-When switching over to Conversion Optimizer, first look at the average CPA of your campaigns instead of just entering your CPA Start with 10% lower than the average CPA on your campaign, and slowly work your way to your target.
-When making bid changes, avoid adjustments larger than 15%. Google’s algorithm doesn’t do well with dramatic changes to the bid, so you must do it in
There you have it! The GDN, managed with smarts and diligence, can be a powerful source of traffic. Try the above process, make sure to schedule those placement and demographic checks, and keep optimizing. Good luck!
ABOUT THE AUTHOR
Sana Ansari has worked in the internet marketing industry since 2009. Prior to joining 3Q Digital in October of 2011, Sana was a PPC Marketing Manager for Quinstreet, leading the insurance vertical.
Before entering internet marketing, she worked as a consultant at Accenture. Sana received a degree in Electrical Engineering from UC Davis. She loves the 2 Bs: baking and badminton.